80s AI photo trend on ChatGPT: Mistakes to avoid for realistic retro photos on Instagram, WhatsApp | Today’s news
The latest image trend in artificial intelligence takes social media back a few decades. From Bollywood-inspired portraits to photos reminiscent of old family albums, users transform their current selfies into 80s-style shots with ChatGPT. The resulting images typically feature film grain, bold colors, dramatic lighting, period hairstyles, and other visual elements associated with the decade.
The trend has spread across platforms including Instagram, where users share their AI-generated retro portraits through posts and reels.
But getting a convincing 80s photo isn’t just a matter of uploading a selfie and asking ChatGPT to make it look old. The wording of the prompt and the visual details entered can greatly influence the outcome.
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OpenAI challenge to create an AI photo from the 1980s
OpenAI shares a challenge that users can use to recreate their mid-80s look.
The challenge asks ChatGPT to preserve a person’s identity and key facial features while changing elements such as their hairstyle, clothing, accessories and surroundings to reflect the period.
Here is the challenge:
“With my uploaded photo, show me what I would have looked like circa 1985. Preserve my identity, facial features, skin tone, age and recognizable look. Transform my hair, clothes, accessories and surroundings with a bold, unmistakable mid-80s style – bold silhouettes, bold accessories, layered details, bold colors and fa18 textures to make it look like direct color and textures. flash and subtle softness Add a period-accurate red and orange date stamp to the bottom corner.
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Mistakes to avoid when creating an AI photo from the 1980s
Simply telling ChatGPT to “make my photo look like it’s from the 80’s” may not provide enough direction for the image.
A more detailed prompt may specify the decade, photographic characteristics, clothing, hairstyles, lighting, colors, surroundings, and other elements that should appear in the resulting image.
- No photographic appearance specification
Clothing and hairstyle alone do not necessarily make an image look like it was photographed in the 1980s.
Details such as analog film grain, faded colors, direct flash, and slight softness can help create the intended vintage photographic aesthetic.
- Forgetting to preserve your identity
AI-generated transformations can change facial features if the challenge focuses too much on changing a person’s appearance.
Specifically, the OpenAI challenge asks ChatGPT to preserve a user’s identity, facial features, skin tone, age, and recognizable appearance while modifying the style around them.
- Keeping modern elements in the picture
A contemporary object can quickly undermine the retro effect.
Users should be specific about removing or avoiding things that don’t fit the intended period, such as smart phones, modern clothing, contemporary backgrounds, or other recognizable modern elements.
OpenAI’s recommended prompt specifically states: “No modern objects or text.”
- No description of the surroundings
By changing the person without dealing with the settings, you can create a shot where the subject looks vintage but the background remains contemporary.
For a more cohesive result, the challenge should also create the desired environment and visual context of the 1980s.
- Too much stylization of the photo
Adding too many exaggerated retro elements can make the result look like an AI-generated interpretation rather than an old photograph.
The trend generally aims to recreate the look of authentic period photography, so visual details should work together rather than overpower the original subject.
- Ignoring small period details
Accessories, colors, textures, hairstyles and silhouettes of clothes – all this can affect whether the image convincingly evokes the eighties.
The OpenAI call therefore calls for “statement additions, layered details, bold colors and textures” alongside broader styling changes.
How to get a more convincing 80s look
The key is to give ChatGPT enough information about what should change and what should stay the same.
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Users can specify the approximate year, photographic style, lighting, colors, clothing, hairstyle, setting, and film properties. At the same time, they can explicitly ask the tool to preserve their identity and recognizable facial features.
The result can then be further refined with additional instructions if certain elements do not match the intended period.
For users participating in the viral trend, the difference between a generic “old photo” and a convincing 1980s recreation largely lies in the level of detail involved in the challenge.
